Data compression techniques are commonly used to achieve a low bit rate in the digital representation of signals for efficient processing, transmission, and storage. The size of seismic datasets, for example, continues to increase due to the need of extracting oil from more complex geologies. This drives demand for better sensor acquisition technologies, higher resolution hydrocarbon models, more iterations of analysis cycles, and increased integration of a broader variety of data types. Thus, seismic data compression has become important in geophysical applications, for efficient processing, storage and transmission of seismic data.
A number of techniques have been proposed for efficient lossless compression of seismic data. U.S. patent application Ser. No. 14/579,130, filed Dec. 22, 2014, now U.S. Pat. No. 9,660,666, entitled “Content-Aware Lossless Compression and Decompression of Floating Point Data,” for example, discloses techniques for content-aware lossless compression and decompression of floating point data, such as seismic data, and other data. The disclosed content-aware lossless compression algorithms employ observed phenomena in the data to obtain improved compression ratios and processing speeds, relative to conventional techniques.
Nonetheless, a need remains for improved compression and decompression techniques in a distributed computing environment.